Paper Infomation
Method for Obtaining Characteristic Parameters of Potato Image Based on Machine Vision
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Author: Zouzou Li, Hongjun Wang, Juntao Xiong, Jianmeng Deng, Yuanhong Li, Weiliang Zhou
Abstract: Potato is the fourth most worldwide crop in the world after wheat, corn and rice. Classification of potatoes is thought to produce greater economic benefits. The current grading methods mainly relies on artificial methods which is not stable and expensive. In recent years, machine vision technologies have been widely used in the field of agriculture, especially achieved great results in the field of agricultural products classification. Machine vision could classify different varieties of agricultural products based on color, volume, quality and other characteristics. For the same variety of potatoes, the shape type and weight range could be graded by the external dimensions. For this purpose, a set of machine vision system was designed, including CCD camera, image acquisition card, computer system, LED light source, two mirrors placed into V type, as well as MATLAB software for image processing and Unscramble software for data analysis. Photos were processed into binary images with MATLAB software. Each number of pixels of target area can be counted as its area. The minimum external rectangle of each target area was obtained for calculating its length and width. The area, length and width were regarded as the image characteristic parameters of the target area. A binary image contains three target areas, for which a photo can be obtained nine characteristic parameters. Data sets based on these characteristics were obtained from 100 potato samples. These data sets were analyzed to verify the correctness of the method with Unscramble software.
Keywords: Machine Vsion System; Three Surface Projections; Image Processing; Minimum Enclosing Rectangle; Image Characteristic Parameters
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